Publication Type : Journal Article
Publisher : International Journal of Recent Technology and Engineering
Source : International Journal of Recent Technology and Engineering, Blue Eyes Intelligence Engineering and Sciences Publication, Volume 7, Number 6, p.56-60 (2019)
Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065976397&partnerID=40&md5=27ad8c5f964ec99a8b5139fdbf18837b
Keywords : CNN, Deep learning, LSTM layer, Tubercle bacillus, Tuberculosis
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Electronics and Communication
Verified : Yes
Year : 2019
Abstract : Tuberculosis or TB, a disease mainly affecting lungs is infected by bacterium mycobacterium tuberculosis and diagnosed by careful examination of microscopic images taken from sputum specimen. Diagnosis of disease using microscopy and computer vision methods are applied for many previous practical problems. Recently, deep learning is playing major role in computer vision applications producing remarkable performance. But, computational complexity always remains as an obstacle in the application of deep learning in many aspects. So in this paper, a shallow CNN with LSTM layer is used for detecting the tubercle bacillus, mycobacterium tuberculosis, from the microscopic images of the specimen collected from the patients. The specified model is producing better performance than state of the art model and also have reduced number of learnable parameters, which requires comparatively less computation than the existing model. © BEIESP.
Cite this Research Publication : A. Simon, Vinayakumar, R., Sowmya, and Dr. Soman K. P., “Shallow Cnn with Lstm layer for tuberculosis detection in microscopic image”, International Journal of Recent Technology and Engineering, vol. 7, pp. 56-60, 2019.